Top Machine Learning Jobs in Tucson, AZ

The Machine Learning Engineer will develop and integrate ML solutions, maintain ML systems, build data pipelines, and collaborate with cross-functional teams.

Analyze biological datasets using machine learning and deep learning, collaborate on research projects, and communicate findings through visualizations and reports.

The AI/ML Specialist Solution Architect Intern will assist in designing AI solutions, learning about distributed workloads, and preparing technical materials, gaining mentorship and exposure to modern ML frameworks and GPU infrastructure.

The Staff ML/AI Platform Engineer will design, prototype and deploy AI/ML models, optimize pipelines, mentor junior engineers, and collaborate closely with other teams to develop machine learning solutions.

Design and implement production-grade ML systems for ICS/OT cybersecurity, build and optimize models (including NLP/LLMs), develop data pipelines and MLOps workflows, collaborate with data teams to deploy and monitor models in cloud and on-prem containerized environments, and troubleshoot production performance and resource issues.

The Senior Product Manager will lead the development of medication prescribing capabilities, utilizing AI and machine learning to enhance member experiences and drive health engagement.

Lead multi-year strategy, roadmap, and execution of Upwork's reputation systems. Own cross-functional delivery of reputation, trust, and ranking initiatives, define success metrics linking reputation to marketplace outcomes, and build and mentor a team of product managers to drive adoption and measurable business impact.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

The Director of Artificial Intelligence will define, lead, and implement AI strategies, managing R&D, building teams, and ensuring ethical AI use to drive business outcomes.

The VP of AI will lead NeoWork's AI strategy, ensuring adoption, developing workflows, building capabilities, and enhancing client value through AI integration.

Lead the implementation of AI-driven supply chain solutions, collaborating with clients to enhance their business processes and ensure seamless technology integration.

Manage and mentor engineers, contribute to product and infrastructure, drive projects, and collaborate cross-functionally to enhance AI platforms.

The role involves defining the vision and strategy of the Outreach AI Platform, prioritizing the roadmap, collaborating with engineering and data science teams, and engaging with customers to refine AI strategies.

Lead ML strategy and standards as a senior individual contributor: define ML infrastructure, tooling, and lifecycle processes; establish monitoring and feature patterns; partner across platform, data, and product teams; mentor data scientists and ML engineers to scale reliable production ML systems.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

The Applied Scientist AI/ML Intern will work on building data pipelines, finetuning LLMs, and deploying AI models in a collaborative team environment.

As a Software Engineer, AI/ML GenAI, you will design and implement AI features, manage embeddings, and optimize AI systems for production deployment while collaborating with product and design teams.

The Sr. Machine Learning Engineer will build tooling and services for ML and generative AI solutions, focusing on deployment, evaluation metrics, and cross-functional collaboration.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

Design, build, and scale ML and Generative AI systems. Develop applications using ML architectures and monitor model performance.

The Staff Machine Learning Engineer will develop AI/ML applications, collaborate with teams to implement models, and leverage a variety of technologies to enhance Twilio's customer support operations.

The Senior Product Manager will lead the strategy for an AI assistant, ensuring compliance and user satisfaction while coordinating with cross-functional teams throughout product development.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.